A Beginning for Mathematics
A University of Toronto professor explores the rapid advancement of AI in mathematics, arguing that while AI may soon surpass human capabilities, the field must adapt its institutions to preserve human understanding. He proposes a positive vision where human mathematical practice evolves alongside automated problem-solving.
Why it matters
This highlights the existential shift in academic research as AI begins to autonomously resolve complex scientific and mathematical problems.
Daniel Litt , professor at the University of Toronto
Three years ago, AI systems could not reliably add two numbers. A year ago, internal models at OpenAI and DeepMind received the equivalent of a gold-medal score on the IMO. Now, these systems are autonomously resolving major open questions. It’s hard to imagine this trend continuing for another year, but I expect it will. It is clear that this will require a radical rethinking of our profession.
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